Lane Line Detection Computer Vision System Applied to a Scale Autonomos Car: AutoModelCar

Abstract

This article introduces a vision system of an autonomous vehicle scaled to detect the lane lines in the Au-toModelCar category of robotics tournaments. The system is developed in C++ using a modular integration architecture in ROS (Robot Operative System) and OpenCV as a computer vision library, embedded in an NVIDIA Jetson Nano card. The system applies image processing, inverse perspective mapping, feature extraction, filtering and modeling of the lane lines by first and second order polynomial regression. The tests that validate the performance of the system are presented.